Instructions to use fbsh96/so101-sock-ball-act-handcam-100eps-mi300x-b16-20000steps with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use fbsh96/so101-sock-ball-act-handcam-100eps-mi300x-b16-20000steps with LeRobot:
- Notebooks
- Google Colab
- Kaggle
SO101 Sock/Ball Pick-Place ACT Hand-Camera Checkpoint
This is a LeRobot ACT checkpoint trained on fbsh96/so101_sock_ball_pick_place_formal_100ep.
Training Summary
- Policy: ACT
- Dataset:
fbsh96/so101_sock_ball_pick_place_formal_100ep - Episodes: 100
- Frames: 91,600
- Device: AMD Instinct MI300X via ROCm/PyTorch
- Steps: 20,000
- Batch size: 16
- Input features:
observation.stateandobservation.images.hand_cam - Action dimension: 12
- Final logged loss: ~0.074
Important Note
This checkpoint intentionally uses only observation.images.hand_cam. The source dataset also contains front_cam, but the raw 720p front camera path was not used in this training run because it was significantly slower without preprocessing/downsampling.
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